The present invention generally relates to the compilation, storage, transfer, retrieval, and aggregation of information. In particular, the invention is an apparatus designed to compile, store, transfer, retrieve, and/or aggregate electronic medically-related records.
The medical community has long sought a method for coordinating and analyzing aggregations of medically-related records. Technical difficulties have prevented the community from designing and implementing a system that permits computerized analysis of medical records. Because medical records are generally non-numerical expressions of concepts and because there is no uniform method of expressing those concepts, computers have traditionally lacked the capacity to recognize when a given medical record satisfies a query.
The community has attempted to design data structures that facilitate computerized classification of medical concepts. A proper data structure must balance the objectives of permitting concepts to be designed with a degree of expressivity, and of facilitating classification of concepts by limiting their complexity. Data structures in the prior art, however, have failed to provide the proper balance of expressivity and complexity to permit efficient coordination and retrieval of medical records.
Many data structures in the prior art lack adequate expressivity. They classify medical concepts according to an alphanumeric code organized in strict hierarchies. A strict hierarchy requires that a single concept have one meaning, one code number, and thus, only one parent concept. The concept must be positioned in one branch of a code-based hierarchical tree.
The SNOMED((trademark)) International work of medical nomenclature is one example of a medical terminology structured according to a strict hierarchy. SNOMED International, which is incorporated herein by reference, is a systemized nomenclature of human and veterinary medicine, which is published, copyrighted and maintained by the College of American Pathologists. SNOMED International is an advanced nomenclature and classification of medical terms and codes.
SNOMED International, and its predecessor SNOMED, provide a detailed and specific coded vocabulary of names and descriptions used in healthcare. Their purpose is to index, store and retrieve information about a patient in a computerized medical record. The original SNOMED, published in 1974, consisted of six nomenclature categories or classes representing various aspects of the human being from a pathophysiologic point of view. These classes include, for example, topography (anatomy), morphology (descriptions of changes in the normal anatomy of the body), etiology (cause or causal agents of diseases or injuries, including drugs and chemicals), function (functions of the human body), disease/diagnosis (general and complex disease terms and syndromes), and procedures (administrative, preventive, diagnostic and therapeutic actions taken to prevent or cure).
SNOMED International, published in 1993, expanded the nomenclature to 11 categories and provided some general linkage modifiers. SNOMED and SNOMED International have been licensed to numerous computer software vendors that have developed customized database applications. An example of the hierarchical constraints of SNOMED International are shown in FIG. 8, which illustrates the classification of the category of diseases by organ system or by the underlying etiology. The present invention, as described in more detail below, eliminates the strictly hierarchical constraints of SNOMED International. FIG. 9 illustrates one type of modification of the relationships of SNOMED International by the present invention.
Strict hierarchies based on alphanumeric codes provide less than satisfactory data structures for compiling, storing, transferring, retrieving, and/or aggregating medical records for two primary reasons. First, the data structure limits the efficacy of queries based upon hierarchical relationships, because medical concepts are complex ideas which are a function of the context of use, and therefore cannot be fully represented solely by a single code. Second, the data structure forecloses the user from forming queries based upon non-hierarchical relationships.
Strict hierarchical structures limit the ability of computers to search medical records according to hierarchical relationships because many medical concepts cannot be properly classified in a single position in a hierarchy. A term that can be described as belonging to several different groups must be encoded into one, and only one, group. One example is the term xe2x80x9cpneumothorax. xe2x80x9d Pneumothorax can be described as a member of the group of terms xe2x80x9cdiseases of the respiratory system,xe2x80x9d or a member of the group of terms xe2x80x9cdiseases of the pleura, mediastinum and diaphragm.xe2x80x9d In SNOMED International, for example, the term xe2x80x9ctraumatic pneumothoraxxe2x80x9d is classified in the class of xe2x80x9cinjuries and poisonings,xe2x80x9d with no link to the class of xe2x80x9cdiseases of the respiratory system.xe2x80x9d
A computer cannot satisfactorily search, sort and retrieve medical records that are organized according to a strict hierarchy. A query for a collection of records classified under a given parent term will not retrieve all pertinent records, when those records contain concepts that were constrained to be positioned in a separate branch of the hierarchy. In the above example, a query in SNOMED International for records of patients with diseases of the lung will not retrieve records of patients afflicted with traumatic pneumothorax, because traumatic pneumothorax was classified under xe2x80x9cinjuries and poisonings.xe2x80x9d
The prior art suffers from an additional limitation in that its data structures do not adequately permit users to search databases according to non-hierarchical queries. Strict hierarchies bundle the meaning of medical concepts into a single alphanumeric code. The code number expresses the relationship of the medical concept to other concepts along the same hierarchical axis, but fails to express the non-hierarchical characteristics of that concept. The code representing the medical concept does not provide information, for example, about how the concept manifests itself or how it is caused. Users cannot enter a query based upon non-hierarchical relationships when the meaning of a concept is contained only in a hierarchical code.
Some disclosed prior art database structures provide a limited ability to search medical records based upon non-hierarchical relationships. These systems, however, leave the meaning of the concepts based in an alphanumeric code, with non-hierarchical linking terms appended to the core meaning. These linking terms are not integrated into the meaning of the term, and do not explicitly define how the linking term relates to the core concept. For example, SNOMED International allows the concept xe2x80x9cacute appendicitisxe2x80x9d to be represented as an appendicitis that is acute, by allowing the user to select the alphanumeric code for the concept xe2x80x9cappendicitis,xe2x80x9d with the alphanumeric code for the concept xe2x80x9cacute.xe2x80x9d It remains unclear, however, whether the term xe2x80x9cacutexe2x80x9d refers to an appendicitis with an acute onset, or an appendicitis with an acute severity.
An ideal data structure for retrieval of medical records needs to offer limited complexity to properly process searches. A surfeit of linking terms restricts the ability of a computer to accurately process a query. The present invention addresses these concerns with a hierarchical structure that includes linkages between more specific child terms and less specific parent terms. At the same time, the present invention provides linkages along non-hierarchical axes or based on non-hierarchical relationships.
The foregoing limitations of prior art data retrieval systems are addressed by the following system for data retrieval of medical records.
The apparatus employs a terminology knowledge base with a data structure specifically designed to permit a classifier to execute subsumption checks upon a database of patient records. In one or more embodiments, the terminology knowledge base is a data structure containing representations of medical concepts. The concepts are formally defined in terms of their hierarchical and non-hierarchical relationships. Concepts are grouped into classes, with a different set of non-hierarchical relationships available to each class. Each concept is assigned an alphanumeric code.
Patient records are entered into a database of encoded clinical records. Each concept expressed in the patient records has an alphanumeric code that is the same as the alphanumeric code of the corresponding concept of the terminology knowledge base.
All concepts in the terminology knowledge base and patient database are expressed according to a description language based upon a set of four operators. This set of operators is sufficient to adequately represent medical concepts and to make inferences about the concepts for the purposes of the electronic medical record. Concepts are vertically linked along a common nomenclature axis in a hierarchical relationship. Concepts are also horizontally linked between different nomenclature axes in a non-hierarchical relationship. Concepts may be horizontally linked to one or more other concepts on different nomenclature axes.
A query manager receives queries and translates the queries into a format processible by the system. Queries are constructed using a standard description language. Queries need not be prespecified, and may seek information based upon hierarchical and non-hierarchical relationships. Queries are processed by a classifier which executes subsumption checks on the patient database to determine which patient records satisfy the query.
In one or more embodiments, the present invention comprises an apparatus for retrieving electronic records from a database of medical records. The apparatus utilizes a knowledge base in the form of a data structure set forth in a description language. The knowledge base includes representations of a plurality of concepts within a plurality of classes. For example, each of the concepts in a first class is vertically linked to another of the concepts in the first class by a parent hierarchical relationship. Each of the concepts in a second class is vertically linked to another of the concepts in the second class by a parent hierarchical relationship. Each of the concepts in a third class is vertically linked to another of the concepts in the third class by a parent hierarchical relationship.
Additionally, some of the concepts in the first class are horizontally linked to another of the concepts in the second class by a non-hierarchical relationship. One or more concepts in the first class are horizontally linked to another of the concepts in the third class by a non-hierarchical relationship.
In operation, a query manager receives a user query and translates the query into the description language. A records analyzer is coupled to the query manager, database and knowledge base. The records analyzer analyzes the records in the database based on the user query and the classes and the hierarchical and non-hierarchical relationships in knowledge base.
In one or more embodiments, the first class includes a plurality of concepts vertically linked in hierarchical relationships with other concepts in the first class, the second class includes a plurality of concepts vertically linked in hierarchical relationships with other concepts in the second class, and the third class includes a plurality of concepts vertically linked in hierarchical relationships with other concepts in the third class.
In one or more embodiments, each of a plurality of the concepts of the second class are horizontally linked to one or more of a plurality the concepts of the third class. The knowledge base can include additional classes, such as a fourth class including a plurality of concepts vertically linked with one another in a hierarchical relationship. Each of a plurality of the concepts of the third class are horizontally linked to one or more of a plurality of concepts of the fourth class. In one or more embodiments, the non-hierarchical relationships comprise a role relationship and the hierarchical relationships include parent relationships, child relationships, xe2x80x9cis-axe2x80x9d relationships and xe2x80x9cpart-ofxe2x80x9d relationships.
In its preferred embodiments, each of the classes of the present invention comprises a nomenclature for medical terminology. The nomenclature for the classes is thus selected from one or more of the group of: (a) diseases/diagnoses, (b) morphology, (c) living organisms, (d) physical agents, activities and forces, (e) chemicals, drugs, and biological products, (f) social context, (g) topography, (h) bodily function, (i) procedures, (j) assessments, (k) spatial relationships,(l) substances, and (m) occupations. Additional classes are possible.
Each of one or more of this group of classes may have one or more associated role relationships. For example, the class of diseases/diagnoses has one or more associated role relationships from the group of: (a) etiology, (b) morphology, (c) course, and (d) severity. The class of topography has one or more associated role relationships from the group of: (a) part-of, (b) branch-of, and (c) tributary-of. Additional associated role relationships are possible.
These and other embodiments are explained in more detail below.